Results 51 to 60 of about 1,915,617 (250)

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

open access: yesTherapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo   +5 more
wiley   +1 more source

Forecasting the Dialysis Burden in Japan: Validation‐Based Projections of Prevalence and Incidence Through 2050

open access: yesTherapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Japan has one of the highest dialysis prevalence rates worldwide and a shrinking, aging population. Whether dialysis burden has entered a sustained post‐peak phase or whether recent declines partly reflect pandemic‐related disruptions remains uncertain.
Hatice Şahin   +2 more
wiley   +1 more source

Organoids in pediatric cancer research

open access: yesFEBS Letters, EarlyView.
Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley   +1 more source

Scalable Time Series Causal Discovery with Approximate Causal Ordering

open access: yesMathematics
Causal discovery in time series data presents a significant computational challenge. Standard algorithms are often prohibitively expensive for datasets with many variables or samples.
Ziyang Jiao, Ce Guo, Wayne Luk
doaj   +1 more source

New permutation algorithms for causal discovery using ICA [PDF]

open access: yes, 2020
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Patrik O Hoyer   +4 more
core  

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

open access: yesFEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Nonlinear causal discovery with latent confounders

open access: yes, 2023
Causal discovery, the task of discovering the causal graph over a set of observed variables X1, ... ,Xm, is a challenging problem. One of the cornerstone assumptions is that of causal sufficiency: that all common causes of all measured variables have ...
David Kaltenpoth (17839733)   +1 more
core   +1 more source

The human gut microbiome across the life course

open access: yesFEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero   +4 more
wiley   +1 more source

Degradation mechanism of the von Willebrand factor A2 domain by nattokinase

open access: yesFEBS Letters, EarlyView.
Nattokinase, a natto‐derived protease, exhibits potent antithrombotic effects. This study demonstrates that nattokinase directly cleaves the von Willebrand factor (vWF) A2 domain in vitro. Unlike the native regulator ADAMTS13, nattokinase degrades folded vWF independently of shear stress.
Ryuichi Hyakumoto   +3 more
wiley   +1 more source

Causal Reinforcement Learning Algorithm Based on Causal Mask [PDF]

open access: yesJisuanji gongcheng
Reinforcement Learning (RL) has become an important solution to sequential continuous decision-making problems, such as root cause localization of fault alarms; however, existing methods suffer from low sample efficiency and high exploration costs that ...
HUANG Siyang, CAI Ruichu, QIAO Jie, HAO Zhifeng
doaj   +1 more source

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